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EEMDelm: Ensemble Empirical Mode Decomposition and Its Variant Based ELM Model

Forecasting univariate time series with different decomposition based Extreme Learning Machine models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>, Parida M, Behera MK, Nayak N (2018). <doi:10.1109/ICSESP.2018.8376723>.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: forecast, nnfor, Rlibeemd
Published: 2022-08-09
DOI: 10.32614/CRAN.package.EEMDelm
Author: Girish Kumar Jha [aut, cre], Kapil Choudhary [aut, ctb], Rajeev Ranjan Kumar [ctb], Ronit Jaiswal [ctb]
Maintainer: Girish Kumar Jha <girish.stat at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: EEMDelm results

Documentation:

Reference manual: EEMDelm.pdf

Downloads:

Package source: EEMDelm_0.1.1.tar.gz
Windows binaries: r-devel: EEMDelm_0.1.1.zip, r-release: EEMDelm_0.1.1.zip, r-oldrel: EEMDelm_0.1.1.zip
macOS binaries: r-release (arm64): EEMDelm_0.1.1.tgz, r-oldrel (arm64): EEMDelm_0.1.1.tgz, r-release (x86_64): EEMDelm_0.1.1.tgz, r-oldrel (x86_64): EEMDelm_0.1.1.tgz
Old sources: EEMDelm archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.